Regulator’s Dialogue Recent Developments in Supervision of

Anti-Money Laundering and Counter-Financing of Terrorism

AML and Financial Crime Risk Division

Enforcement and AML Department

Hong Kong Monetary Authority

7 June 2018

Disclaimer

The presentation is provided for training purposes and does

not form part of the formal legal and regulatory requirements

of the HKMA. It should not be substituted for seeking

detailed advice on any specific case from an AI’s own

professional adviser.

The HKMA and HKIB are the co-owners of the copyright and

any other rights in the PowerPoint materials of this

presentation. These materials may be used for personal

viewing purposes or for use within an AI. Such materials

may not be reproduced for or distributed to third parties, or

used for commercial purposes, without prior written consents

of the HKMA and HKIB.

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Agenda

Using Hong Kong’s ML/TF risk assessment in the risk-based

approach

Strengthening information & intelligence sharing

Effectiveness in manging sanctions risks

Harnessing the potential of technology in AML/CFT work

The FATF Mutual Evaluation of Hong Kong – implications for

the banking sector

3

Agenda

Using Hong Kong’s ML/TF risk assessment in the risk-based

approach

Strengthening information & intelligence sharing

Effectiveness in manging sanctions risks

Harnessing the potential of technology in AML/CFT work

The FATF Mutual Evaluation of Hong Kong – implications for

the banking sector

4

Risk Assessment Report

Covers 12 sectors including financial

sub-sectors and non-financial sectors

Published in April 2018

(https://www.fstb.gov.hk/fsb/aml/en/d

oc/hk-risk-assessment-report_e.pdf)

Examines the ML/TF threats and

vulnerabilities facing various sectors

and Hong Kong as a whole

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Hong Kong’s AML/CFT Policy

The Government is committed to upholding a robust AML/CFT regime

that:

a) Fulfills the international AML/CFT standards;

b) Deters and detects illicit fund flows;

c) Combats ML/TF and restrains and confiscates illicit proceeds

effectively;

d) Reduces ML/TF vulnerabilities in Hong Kong;

e) Adopts a risk-based approach (RBA) in applying compliance

obligations to businesses and individuals;

f) Fosters strong external and international collaboration to disrupt

global ML/TF threats; and

g) Promotes awareness and builds capacity of private sector

stakeholders in combatting ML/TF risks.

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Enhancing the AML/CFT Regime

Five major areas of work:

a) Enhancing AML/CFT legal framework to address gaps in legislation;

b) Strengthening risk-based supervision to ensure targeted regulation

of riskier areas;

c) Sustaining outreach and capacity-building to promote awareness

and understanding of ML/TF risks;

d) Monitoring new and emerging risks; and

e) Strengthening law enforcement efforts and intelligence capability to

tackle domestic and international ML/TF, and enhance restraint and

confiscation of the proceeds of crime.

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Relevance for AIs (1)

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Vulnerability level, threat level and overall ML risks of financial sectors

Source: Figure 5.1 of Hong Kong Money Laundering and Terrorist Financing Risk Assessment Report

Key results for the banking sector

Main threats

Fraud, tax evasion, corruption, sanctions evasion

Threats arise from domestic and, to a greater extent, external

activities

Vulnerabilities

ML/TF vulnerabilities exist in various segments and banking

products / services

Private banking, trade finance, international funds transfer

and retail and corporate banking

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Relevance for AIs (2)

Major Predicate Offences

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Breakdown of 1,621 identified predicate offences associated with 1,908

ML cases in 2011 - 2015

Source: Figure 4.1 of Hong Kong Money Laundering and Terrorist Financing Risk Assessment Report

FATF Recommendation 1 – Assessing

Risks & Applying a Risk-based Approach

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Identify,

assess and

understand

ML/TF risks

Formulate

better

targeted

response to

ML/TF risks

Apply an

RBA in

developing

AML/CFT

policies

Expectations

Institutional Risk Assessment (IRA)

No assumption of “replicating the Risk Assessment results” in

conducting AIs’ own IRA:

– a “high” ML risk level for the banking sector does not mean each

AI’s IRA result must also be “high”

AIs should take into account the main threats and vulnerable

areas of business identified in the Risk Assessment

AIs should study the Risk Assessment Report carefully,

consider relevant insights and implications, review and update

IRA according to your business model

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Areas of Further Work

13

Sanctions

compliance

Reduce

compliance

burden

Public –

private

partnership

Innovation

and use of

technology

Regulatory

cooperation

Strengthening

ML/TF risk

understanding

Risk-

Based

Approach

Agenda

Using Hong Kong’s ML/TF risk assessment in the risk-based

approach

Strengthening information & intelligence sharing

Effectiveness in manging sanctions risks

Harnessing the potential of technology in AML/CFT work

The FATF Mutual Evaluation of Hong Kong – implications for

the banking sector

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Hong Kong’s AML/CFT Policy

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A major area of work to enhance Hong Kong’s AML/CFT

regime:

Strengthening law enforcement efforts and intelligence

capability to tackle domestic and international ML/TF,

and enhance restraint and confiscation of the proceeds

of crime, including through multi-agency cooperation/

partnership

Information & Intelligence Sharing

HKMA working together with Joint Financial Intelligence

Unit (JFIU), Hong Kong Police Force (HKPF) and

banking sector in two work streams

– Strengthening public-private information and intelligence sharing

on serious financial crimes and ML/TF activities

Circular on “Strengthening Information and Intelligence

Sharing” issued on 10 May 2018

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Suspicious Transaction Reports

(STRs)

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The growing number of STRs

Source: Figure 3.3 of Hong Kong Money Laundering and Terrorist Financing Risk Assessment Report

Suspicious Transaction Reports

(STRs)

Revised “Guidance Paper on Transaction Screening,

Transaction Monitoring and STR Reporting” [May 2018]

– Take into account recent experience and, in particular, analysis

and comments from JFIU

– AIs expected to conduct gap analysis and effect necessary

process changes

– Objective should be consistent, systematic approach

– Proactive in enhancing STR reporting

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Fraud and Money Laundering

Intelligence Taskforce (FMLIT)

A public-private partnership for sharing information on cases

and typologies

Assists in the detection, prevention and disruption of crime in

a more targeted way

– Greater collective understanding of risks

– More informed, risk-based decision making in allocating private

sector AML/CFT resources

Industry support for FMLIT essential to its success

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Agenda

Using Hong Kong’s ML/TF risk assessment in the risk-based

approach

Strengthening information & intelligence sharing

Effectiveness in manging sanctions risks

Harnessing the potential of technology in AML/CFT work

The FATF Mutual Evaluation of Hong Kong – implications for

the banking sector

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Overview

Geopolitical developments

Increasing complexity of sanctions

HK vulnerable to abuse as conduit for illicit funds

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Recent Initiatives

“Anti-Money Laundering / Counter-Terrorist Financing: United

Nations Sanctions” – Jan 2018

“FATF Guidance on Counter-Proliferation Financing”; and

discussion with stakeholders – March 2018

“Feedback from Thematic Reviews of AIs’ Sanctions

Screening Systems”; providing industry guidance after

thematic reviews – April 2018

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Thematic Review - Background

Review of automated sanction screening systems

– Assistance from Regtech firm

Conducted on selected AIs

Assessing the effectiveness and efficiency of

screening systems

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Testing Process – Key Aims

Effectiveness

Whether systems generate alerts on un-manipulated names

Whether “fuzzy matching” rules are effective at matching

manipulated names

Efficiency

Whether false positive levels are within operable levels

Comparison with industry standards

Whether system performance is in line with AI’s expectations

and how it fares compared to its peers

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Expectations: Senior Management

Consider risk of sanctions breaches, determine

appropriate level of sanctions screening to manage risk

– Proven methodology for determining system settings and

performance

– Justifying deviations from group-wide policies

Role of Management Information

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Expectations: Testing on New

Systems / Upgrades

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AIs are required to demonstrate thorough testing and

tuning before system deployment and upgrades

Documentation of testing and analysis

Expectations: Frequent Ongoing

Monitoring, Testing & Tuning

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Adequate understanding of obligations under HK and

other overseas sanctions regimes (as applicable)

Ongoing testing on system effectiveness and efficiency

Expectations: Adequate Skills &

Knowledge

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Clear and demonstrable understanding of system filters

employed in the institution’s screening technology

Clarity around ownership and accountability of risk

Monitoring of suppression / good guy / white lists

Expectations: Achieving System

Effectiveness & Efficiency

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Understanding relationship between effectiveness and

efficiency

– e.g. Monitoring levels of false positives while maintaining

accuracy

Demonstrating reasoning for rules or threshold changes

implemented to deal with levels of false alerts

Concluding Remarks

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Significant legal and reputational risk of operating

ineffective sanctions screening systems

Cost of inefficient screening systems should not be

underestimated

The objective of this exercise is to provide AIs with the

right information needed to optimize system

performance

Regular system testing is vital for AIs

Agenda

Using Hong Kong’s ML/TF risk assessment in the risk-based

approach

Strengthening information & intelligence sharing

Effectiveness in manging sanctions risks

Harnessing the potential of technology in AML/CFT work

The FATF Mutual Evaluation of Hong Kong – implications for

the banking sector

31

Use of New Technologies

New technologies have created opportunities for

criminal activity

The same technologies, when used for good, have

huge potential to detect and disrupt crime

– Machine learning

– Artificial intelligence

– Robotics

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Regulatory Thinking

Risk-based / technology-neutral approach to supervision

Objective is to ensure adequate protection for sector

integrity and for customers while retaining appropriate

flexibility so as not to hinder the development of Fintech

– No fixed way of doing things, open minded – interested in what

works and is effective

– Ability to maintain close contact with the industry and other

stakeholders to understand latest developments

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Regulatory Engagement

Collaboration – with internal, external partners and with

the technology sector is important

HKMA’s response:

– Fintech Supervisory Chatroom

– Banking Made Easy initiative

– Greater flexibility under amended AMLO

– FMLIT

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Response must recognize the increasingly proactive

role of AIs

– The nature of that role has also changed as crime increasingly

moves “online”

Threat in ML/TF risk assessment:

– Cybercrime threats, together with rapid advances in financial

services technology, which have created new avenues for ML

Efficiency and the willingness to innovate

– How can we get better at achieving the desired outcome?

Encouraging Innovation

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Agenda

Using Hong Kong’s ML/TF risk assessment in the risk-based

approach

Strengthening information & intelligence sharing

Effectiveness in manging sanctions risks

Harnessing the potential of technology in AML/CFT work

The FATF Mutual Evaluation of Hong Kong – implications for

the banking sector

36

Hong Kong’s Mutual Evaluation (ME)

Assess technical compliance with the FATF Standards

and level of effectiveness of AML/CFT systems

H2/2018 to H1/2019 (last ME 2007 – 2008)

Work with Government and other agencies in

preparation including

– published Hong Kong’s ML/TF Risk Assessment Report in April

– Update of information on technical compliance and

effectiveness

– Preparatory work for the on-site visit of the assessment team

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Hong Kong’s ME – Banking Sector

Expected to be a major focus given the size and

importance in Hong Kong’s economy

HKMA continues to accord a high priority to AML/CFT

work

– Work closely with all relevant stakeholders, domestically and

internationally, to develop and provide responses that are agile

and adaptable

– Recognise innovation and making the best use of technology

– Ensure response always relates to effectiveness

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Hong Kong’s ME – On-site Visit

October to November 2018

– Process has already started

Assessors will meet with representatives of banking

sector

– To assess the effectiveness and discuss risks

– Not an investigation nor an inspection of individual private

sector entities

– Briefings will be arranged for selected representatives

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Immediate Outcome 4 – FIs and DNFBPs adequately

apply AML/CFT preventive measures commensurate with

their risks, and report suspicious transactions

How well do FIs and DNFBPs

– Understand their risks and obligations and apply mitigation

measures commensurate with these risks?

– Apply CDD and record keeping measures?

– Apply the enhanced or specific measures for (a) PEPs, (b)

correspondent banking, (c) new technologies, (d) wire transfers

rules, (e) targeted financial sanctions relating to TF and (f)

higher risk countries identified by the FATF?

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Q&A

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